Did you come into Python from a computational science side of things?

Were you just looking for something better than Excel and Matlab and you got pulled in by

all the Python has to offer?

That's great.

But following that path often means some formal practices from software development weren't

part of that journey.

On this episode, you'll meet Martin Haru, who does data science in the context of

academic research. He's here to share his best practices and lessons for data scientists of all

sorts. This is Talk PythonMe, episode 252 recorded January 30th, 2020.

Music Welcome to Talk Python to Me, a weekly podcast on Python, the language, the libraries, the ecosystem, and the personalities.

This is your host, Michael Kennedy. Follow me on Twitter

where I'm at M. Kennedy. Keep up with the show and listen to past episodes at talk python.fm,

and follow the show on Twitter via at talk python. This episode is sponsored by Clubhouse and

Linode. Please check out what they're offering during their segments. It really helps support

the show. Hey, everyone,

a couple of announcements. First, I have a very exciting new course that we just launched this week.

If you've always wanted to solidify your programming foundations and get into Python, but you've never had the chance to take a computer science course, I built a course for Hugh. It's called

Python for the Absolute Beginner. It's called Python for the absolute beginner.

It's for absolute beginners because we start from the very beginning. How to install Python,

what is a variable, why do we need loops, and so on. And then we go on to build some really fun

projects that will teach you 80% of the Python language. Another challenge people run into when

learning programming is having

...